The basic operation and structure of communication systems, such as cellular radio telephone systems communication systems and land mobile communication systems, are well known in the art. Communication systems typically comprise a plurality of communication units, a predetermined number of base stations (or repeaters) located throughout a geographic region and a controller. The communication units may be vehicle mounted or portable units. The communication units and the base stations each comprise either a transmitter or a receiver or both to form a transceiver. The communication units are coupled to the base stations by a communication channel over which modulated signals, such as radio frequency (RF) signals, are transmitted and/or received. The controller comprises a centralized call processing unit or a network of distributed controllers working together to establish communication paths for the communication units in the communication system.
More particularly, a receiver of the communication unit receives a modulated signal subsequent to transmission thereof by a transmitter of the base station on the communication channel. The receiver includes, inter alia, a downconvertor, a sampler, a memory unit, a correlator and a detector. The downconvertor downconverts the modulated signal to produce a downconverted signal. The sampler samples the downconverted signal at multiple points in time to produce a sampled signal. The memory unit stores a reference signal. Both the modulated signal and the reference signal are complex signals represented by real and imaginary components defined by real and imaginary axes. The correlator correlates, at the multiple points in time, the sampled signal with the reference signal to produce a complex correlation signal. The complex correlation signal is used, inter alia, for synchronization, signal recovery and channel sounding.
A well known technique for correlating the complex sampled signal with the complex reference signal to produce a complex correlation signal is derived in the following equations EQ1-3. ##EQU1## Wherein S(n) and Rx(n) are defined by: EQU S(n)=s.sub.r (n)+js.sub.i (n) EQU Rx(n)=rx.sub.r (n)+jrx.sub.i (n)
Expanding the real and imaginary components in EQ 2 results in: ##EQU2## Wherein Rx(n) is the sampled signal, S(n) is the reference signal signal, C.sub.n is the complex correlation signal and k is an index, from zero to fourteen, for example. Both the sampled and reference signals are complex signals having real and imaginary components. The correlation technique is typically performed by a finite impulse response filter in a hardware or software implementation. As shown in EQ 3, the complex correlation signal for each index has four multiply operations and two add operations. It is well known that implementing hardware to perform the multiply operations is parts intensive which is costly, space consuming and current drain sensitive. Likewise, implementing software to perform the multiply operations is instruction intensive which is current drain sensitive.
Therefore, there is a need for a complex signal correlator and method therefor of reduced complexity.